The present invention relates to character recognition systems and, more particularly, to character recognition systems for automatically recognizing characters written on paper.
FIG. 18 shows a system for recognizing characters in contact with one another. In this system, contact portions of characters in a character pattern are detected, and the pattern is separated at the detected contact portions into character candidates, and kinds of the separated character candidates are determined in a character recognition mean.
Specifically, the illustrated character recognition system comprises a character row extracting means 101 for extracting an area of one character row, a character candidate separating means 201 for separating areas each corresponding to one character, a character recognition means 301 for recognizing each character candidate separated in the character candidate separating means 201, and a recognition result verifying means 401 for verifying the result of recognition executed in the character recognition means 301.
Japanese Patent Laid-Open No. 59-098283 discloses a pattern separating and recognizing system as a first example of the character recognition system having the above construction. In this system, character separation result data which are obtainable for, for instance, a contact character pattern as shown in FIG. 19, as outputs of the character candidate separating means 201 and include incorrect character data, are registered in a character recognition dictionary 302. When a candidate character pattern hits the dictionary obtained from the incorrect character separation result, the character recognition means 301 provides data representing the kind of the hit character and also data representing that the hit character is obtained by separating the pattern at incorrect position, i.e., an incorrect partial pattern. The recognition result verifying means 401 provides recognition result data when and only when it verifies that both the results of recognition of the left and right separated character candidates are not partial patterns.
In FIG. 19, the three arrows show examples of the character candidate separating position. Assuming that the right end arrow represents the correct separating position, when the pattern separation is performed at this position, the means 401 verifies that both the recognition results of the left and right separated character candidates are not partial patterns ("0"), and provides data "00".
Japanese Patent Laid-Open No. 8-16720 discloses a second example of the prior art character recognition system. In this system, the character candidate separating means 201 separates a contact character pattern at a minimal position, which is detected from a horizontal projection profile of a character row pattern. When no minimal position is detected from the profile, the contact character pattern is collectively recognized without separating it. To this end, the character recognition means 301 has a special structure that can collectively recognize, without separation, a pattern which is incapable of being separated by using the projection profile, and reference patterns for contact characters are stored in the character recognition dictionary 302.
Japanese Patent Laid-Open No. 1-181176 discloses a third example of the prior art character recognition system. In this character recognition system, the character candidate separating means 201 includes means for detecting characters not in contact with other characters, and means for detecting the contact characters. In this latter system, unlike the preceding second example of system, the separating position is not absolutely determined by using a pure horizontal projection profile of the character row pattern. Instead, a contact character pattern is divided into two divisions for each pixel in the horizontal direction. A position is then detected, which provides the best mean evaluation value of the recognition results obtained, and the pattern is separated at this position.
In any of the above three prior art character recognition systems, a plurality of separated character candidates are prepared for each contact character pattern, and the best combination of these candidates is selected as a character recognition result.
However, as shown in FIG. 20, depending on the way of separated character candidate selection, it is possible that the character recognition means recognizes a wrong character as a result of pattern separation at a wrong separating position. In the case of FIG. 20, the character recognition means erroneously recognizes the right character candidate to be figure "2".
As described above, the above prior art character recognition systems have a high possibility that the character recognition means erroneously recognizes a wrong character kind from a character candidate pattern obtained by separating a contact character pattern at a wrong separating position.